Commit Graph

5 Commits

Author SHA1 Message Date
Tom Ritchford
d25e6e623f Fix unused Python variables in test/[a-d]* (#134665)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/134665
Approved by: https://github.com/albanD
2024-12-13 22:13:12 +00:00
snahir
16ea0ddcdb Ignore logger methods to avoid graph breaks (#139403)
Fixes #132635

Calls to logging.logger cause a graph break, this PR allows the user to avoid these graph breaks (for specific methods) by setting DISABLE_LOGS_WHILE_COMPILING to 1.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/139403
Approved by: https://github.com/williamwen42
2024-12-05 20:12:26 +00:00
angelayi
c844b377fa [dynamo] Reorder logs (#116106)
Currently when there is a print/warning in the graph, dynamo graph breaks causing export to fail. However export would like to just skip over these print/warning calls: https://github.com/pytorch/pytorch/issues/113792.

Additionally there's a torch.compile feature request to "reorder prints" so that instead of graph breaking when hitting prints/logging, we can skip over these prints to create larger compiled graphs, and then print the results out after those compiled graphs: https://github.com/pytorch/pytorch/issues/93739. This PR also adds the `reorderable_logging_functions` config for users to register logging functions to be reordered (like `print` or a custom logging function). Printout of the bytecode after reordering the prints looks like the following: P914736600

There are some limitations to the printing right now:
* You can only register logging functions, not methods
* Inputs to the logging functions can only be tensors, constants, and format strings
* Inputs to the logging functions which will later be mutated in-place will not be printed correctly

TODO: Add the following tests
* print function with argument of nested data structure;
* print function with argument of nested data structure being updated inside of compile region (this would test if we handle side effect correctly);
* custom defined logging functions with nn.Module or nn.Module attribute arguments;
* custom defined logging functions with submodule input/output as arguments (we need to handle the mapping and fused-out value);
* custom defined logging functions with tensor argument and mutation inside of the function (TBD: this may increase memory usage);

Pull Request resolved: https://github.com/pytorch/pytorch/pull/116106
Approved by: https://github.com/yanboliang
2024-03-01 17:04:24 +00:00
PyTorch MergeBot
63b259492a Revert "[dynamo] Reorder logs (#116106)"
This reverts commit c5472628ff.

Reverted https://github.com/pytorch/pytorch/pull/116106 on behalf of https://github.com/clee2000 due to landrace with 342e7929b8, which removed the import for warnings.  Should be an easy fix after rebase c5472628ff ([comment](https://github.com/pytorch/pytorch/pull/116106#issuecomment-1972586180))
2024-03-01 06:25:46 +00:00
Angela Yi
c5472628ff [dynamo] Reorder logs (#116106)
Currently when there is a print/warning in the graph, dynamo graph breaks causing export to fail. However export would like to just skip over these print/warning calls: https://github.com/pytorch/pytorch/issues/113792.

Additionally there's a torch.compile feature request to "reorder prints" so that instead of graph breaking when hitting prints/logging, we can skip over these prints to create larger compiled graphs, and then print the results out after those compiled graphs: https://github.com/pytorch/pytorch/issues/93739. This PR also adds the `reorderable_logging_functions` config for users to register logging functions to be reordered (like `print` or a custom logging function). Printout of the bytecode after reordering the prints looks like the following: P914736600

There are some limitations to the printing right now:
* You can only register logging functions, not methods
* Inputs to the logging functions can only be tensors, constants, and format strings
* Inputs to the logging functions which will later be mutated in-place will not be printed correctly

TODO: Add the following tests
* print function with argument of nested data structure;
* print function with argument of nested data structure being updated inside of compile region (this would test if we handle side effect correctly);
* custom defined logging functions with nn.Module or nn.Module attribute arguments;
* custom defined logging functions with submodule input/output as arguments (we need to handle the mapping and fused-out value);
* custom defined logging functions with tensor argument and mutation inside of the function (TBD: this may increase memory usage);

Pull Request resolved: https://github.com/pytorch/pytorch/pull/116106
Approved by: https://github.com/yanboliang
2024-03-01 04:48:44 +00:00